Song Units Research Articles

Vocal complexity in a socially complex corvid: gradation, diversity and lack of common call repertoire in male rooks.

Vocal communication is widespread in animals, with vocal repertoires of varying complexity. The social complexity hypothesis predicts that species may need high vocal complexity to deal with complex social organization (e.g. have a variety of different interindividual relations). We quantified the vocal complexity of two geographically distant captive colonies of rooks, a corvid species with complex social organization and cognitive performances, but understudied vocal abilities. We quantified the diversity and gradation of their repertoire, as well as the inter-individual similarity at the vocal unit level. We found that males produced call units with lower diversity and gradation than females, while song units did not differ between sexes. Surprisingly, while females produced highly similar call repertoires, even between colonies, each individual male produced almost completely different call repertoires from any other individual. These findings question the way male rooks communicate with their social partners. We suggest that each male may actively seek to remain vocally distinct, which could be an asset in their frequently changing social environment. We conclude that inter-individual similarity, an understudied aspect of vocal repertoires, should also be considered as a measure of vocal complexity.

First song description of the humpback whales, Megaptera novaeangliae (Balaenopteridae: Artiodactyla), breeding off Nicaragua

Introduction: Humpback whales belonging to the Central American (CA) Distinct Population Segment breed off the Pacific coast of Nicaragua. Knowledge on this endangered population and its conservation status is limited.
 Objective: The aim of this study is to provide the first description of the CA humpback whale song off Nicaragua, which helps further understanding on the population’s dynamics.
 Methods: Acoustic recordings of songs were obtained during dedicated boat-based surveys at two locations on the Pacific coast of Nicaragua in 2018. Recordings were made from the boat using a portable system for a total of 23 hours and 56 minutes over 32 days from January to April 2018. A total of nine recordings of high enough quality for the song analysis were identified during this period from three different days at Padre Ramos (PR) (northern site) and four different days at San Juan del Sur (southern site). Song structure was described using standard humpback whale song elements, i.e. themes, phrases, and units.
 Results: A total of seven themes, seven phrases, and 19 unit types were identified. Three of the themes were common and frequently repeated in a song cycle while the others were less common in the repertoire and were recorded only during the middle of the season. Song theme order was variable, both within and across song sessions.
 Conclusions: This study provides the first song description of humpback whales along the Pacific coast of Nicaragua. Comparison of these songs with other datasets from the CA population and other breeding areas in the Northern Hemisphere could help understand the migratory patterns of these animals and the level of connectivity among populations since song can be socially learnt. Future data collection of humpback whale song recordings in Nicaragua is necessary to gain further understanding on the song structure variation within this population and the mechanisms of song transmission and dynamics across populations in the region.

Sub-unit classification of Pacific and Atlantic humpback high-complexity song units—Sub-unit diversity drives unit diversity

Humpback whale communication studies have primarily focused on holistic unit classification methods to identify thematic patterns of song structure. These various whole-unit, spectral-feature-extraction and classification procedures have resulted in low information entropy estimates of songs, akin to bird song. A recent study of high complexity, frequency-modulated song units shows that unit diversity and information entropy of humpback vocalizations is much higher and variable across regions of the Pacific and the Atlantic. Sub-unit-level feature-extraction and classification of these high-complexity units indicates that humpbacks have precision control of the generation of target frequencies, a characteristic of human vowel production. The number of distinct sub-units varies by geographic region and is comparable to English and Asian language phoneme sets.

Variability in Temporal Characteristics of the South Eastern Indian Ocean Pygmy Blue Whale Song

The temporal characteristics of whale song are considered to be amongst the most stable elements of song production, though very few studies have looked at the timing of discrete sounds or the silences between them. This study indicates that the temporal characteristics of the song of the southeast Indian Ocean pygmy blue (SEIOPB) whale are highly variable. While the song repetition interval, or inter-song interval (ISI), appeared to remain consistent within a song event, defined as a consistent bout of singing presumed to come from an individual animal, it was found to be variable between song events. Song structure was a confounding factor in the analysis of variability in ISI with songs comprised of longer phrases naturally having a longer song repetition interval. The songs of the SEIOPB whale are characteristic of the species with only three primary song types. The three-unit song (units I, II and III) has the longest mean ISI of ~ 200 s, approximately twice that of songs composed of only two units (II and III) at a mean of ~ 100 s ISI which is approximately twice the ISI of a one-unit song (unit II only). The results of this study suggest that variability in ISI cannot be attributed to change in one element of a song but is driven by temporal changes in all elements of the song including phrase structure, unit duration and the length of the intervals between song units. Thus, the temporal characteristics of blue whale song appear to be under the control of the animal and may vary between individual whales, and within songs of an individual. It is concluded that the temporal characteristics of song potentially encode contextual information about the singer and may be influenced by audience effects, including audience composition and singer density.

The Implementation of a Module “Sahabatku Indonesia” in Favorite Song Units on the Speaking Skills of BIPA Students

Indonesian for Foreign Speakers (BIPA) is an Indonesian language teaching program whose teaching subjects are foreign speakers. The BIPA learning process certainly requires an appropriate and interesting curriculum, teaching materials, and learning methods for the success of foreign speakers in achieving learning goals. The research objective was to find out and describe the effect of the Indonesian best friend module in favorite song units on speaking skills at BIPA level 7. The research method used by researchers is descriptive qualitative. Researchers will describe a data analysis with the method used is descriptive. The data collection technique used is the form of collecting data by observing students. The results of observations on the material in the Indonesian best friend module activities are designed according to level, one of which is the advanced level for students who can already speak Indonesian, namely using the best friend Indonesia BIPA level 7 module which includes the favorite song units. In this study, the researcher refers to SKL (Graduation Competency Standards) at BIPA Level 7 through a Module that focuses on aspects of speaking skills in BIPA learners. The results of this research make students interested in the learning provided by the teacher in using the best friend module Indonesia BIPA level 7 favorite song unit and students prefer speaking skills because learning through speaking skills makes students more active, it is very fun to sing together the same as the title of the song "Laskar Pelangi" by Nidji and understand every meaning and vocabulary in the lyrics of the song.

Assessing intra-individual consistency in humpback whale song production using animal-borne acoustic recorders

Studying individual variation in vocal behavior can provide insight into its functions, stability, and mechanisms. Collecting such data at the scale of the individual can be facilitated using animal-borne tags. Here, we use archival suction-cup acoustic recording tags to investigate intra-individual variation in male humpback whale song production. Humpback whale song is a complex and hierarchically structured vocal sequence of 4-7 repeated phrases that are comprised of different units. Repeated songs are termed song sessions. To investigate how consistent song production is within the song session of an individual whale, we deployed suction cup-attached acoustic recording tags on humpback whales in the Hawaiian Islands Humpback Whale National Marine Sanctuary during the 2018–2022 breeding seasons. We analyzed tag data from nine whales to assess intra-individual variation in song structure and syntax as well as differences in the acoustic properties of song units across each song iteration. Each tag contained between 4 and 24 song iterations, and song session recordings varied between 45 minutes and 5 hours. Across individuals, the most variable song iterations occurred at the beginning of a song session. All individuals showed variation in syntax and unit production throughout a session; however, some singers were more consistent than others.

Sexually Distinct Song Cultures Across a Songbird Metapopulation

Songbirds learn their songs culturally, through imitating tutors. The vocal culture of a songbird population changes as new song units (syllables) are introduced through immigration, copying errors, and innovation, while other syllables fall out of use. This leads to a diversification of the syllable pool across the species, much like the diversification and spatial patterns of human language. Vocal cultures have been well-studied in male songbirds but have been largely overlooked in females. Here we undertake one of the first comparisons of male and female song cultures across a songbird metapopulation—studying New Zealand bellbirds Anthornis melanura spanning a network of six islands. Having classified 20,700 syllables (702 types), we compare population syllable repertoire sizes and overlap between sites and sexes. We show that males and females—both with complex songs—have distinct song cultures, sharing only 6–26% of syllable types within each site. Furthermore, male and female syllable types can be statistically discriminated based on acoustic properties. Despite diverse syllable repertoires within sites, few syllable types were shared between sites (both sexes had highly distinct site-specific dialects). For the few types shared between sites, sharing decreased with distance only for males. Overall, there was no significant difference between sexes in degree of site–site repertoire overlap. These results suggest different cultural processes at play for the two sexes, underlining the inadequacy of male-centric song research and calling for comparisons of male and female song cultures in many more species.

Frequency changes in humpback whale (Megaptera novaeangliae) song units in response to small boat noise Astarte Brown Advised by Kerri D. Seger

Anthropogenic noise compromises the effectiveness of communication in marine animals. This can interfere with natural auditory signal processing (for example, “masking”). Some animals have been shown to change the frequencies of their vocalizations to avoid masking. Humpback whales produce songs with low fundamental frequencies which often overlap with the low frequency content of vessel noise. In the Gulf of Tribugá, a part of the breeding grounds for humpback whale Stock G, a marine port construction project has been proposed. If constructed, underwater noise would significantly increase and potentially cause acoustic behavioral changes, negatively impacting communication efforts among the whales. This study was supported by SURIEA, and tested whether humpback whales in the Gulf of Tribugá changed the frequency content of their songs during and after boat noise as compared to before it was present. Out of 38 comparisons, song frequencies significantly changed 9 times. Additionally, out of 20 comparisons, bandwidth narrowed 11 times, broadened 9 times, shifted higher 6 times, and shifted lower 2 times. These results give greater insight into how humpback whales are able to adjust their song structure in response to small boat noise and indicate that adaptations to some anthropogenic noise sources are possible.

The whale song translation project—An experiment to assess humpback whale response to voice-selected visual feedback cues

To better understand the behavioral and communication capabilities of Megaptera Novaeangliae, the findings of a recent whale song study suggest an intriguing experiment to assess humpback whale response to acoustically selected visual-feedback cues. The analysis of high-complexity, frequency-modulated song units indicates a Shannon-Hartley-compliant sub-unit architecture similar to human vowel generation. Like constant-pitch English language vowels, which are differentiated by their two most energetic peak resonance frequencies, humpbacks also exhibit precision vocal control of the production of a variety of sub-units of distinct and differentiable harmonic frequency combinations. Humans navigate mobile phone and tablet-PC informational, gaming, and adaptive learning apps using visual feedback from tactile-selected touchscreen icons and hyperlinks. In lieu of tactile manipulation, an alternative approach to touchscreen control is vocal selection of icons and links corresponding to the generation of specific vowel resonance frequencies and sub-unit harmonic frequencies. A software prototype of a voice-controlled “touchscreen” gaming experiment demonstrates how humans and humpback whales could conceivably interact or how humpbacks could engage in informational transactions. The prototype also incorporates video “training” examples designed to guide subjects in the voiced selection of visual symbols assigned to the sub-regions of a big-screen display.

Acoustic metrics to assess humpback whale song unit structure from the Atlantic sector of the Southern ocean.

Acoustic metrics (AMs) aggregate the acoustic information of a complex signal into a unique number, assisting our interpretation of acoustic environments and providing a rapid and intuitive solution to analyze large passive acoustic datasets. Manual identification and characterization of intraspecific call trait variation has been largely used in a variety of sonic taxa. However, it is time consuming, relatively subjective, and measurements can suffer from low replicability. This study assesses the potential of using a combination of standardized and automatically computed AMs to train a supervised classification model, as an alternative to discrimination protocols and manual measurements to categorize humpback whale (Megaptera novaeangliae) song units from the Southern Ocean. Our random forest model successfully discriminated between the 12 humpback whale unit types (UT), achieving an average classification accuracy of 84%. UTs were further described and discussed in the context of the hierarchical structure of humpback whale song in the Southern Ocean. We show that accurate discriminant models based on relevant AM combinations provide an interesting automated solution to use for simple, rapid, and highly reproducible identification and comparison of vocalization types in humpback whale populations, with the potential to be applied to both aquatic and terrestrial contexts, on other vocal species, and over different acoustic scales.

Comparing the Acoustic Behaviour of the Eastern Indian Ocean Pygmy Blue Whale on Two Australian Feeding Grounds

Long-term data of underwater passive acoustic monitoring (PAM) collected from two sites of pygmy blue whale presence within Australia, the continental shelf off Portland (38.5° S, 141.2° E) and the Perth Canyon (32° S, 115° E) were analysed to compare the acoustic behaviour of eastern Indian Ocean pygmy blue (EIOPB) whales. Pygmy blue whale song detection was consistently higher at the Perth Canyon site than at the Portland sample site. Statistical analysis found there to be a significant difference in the production of song and phrase variants between sites (p < 0.01) with a shorter two-unit (P2) song variant being more common in the Perth Canyon area, while the traditional three-unit (P3) song variant was more frequent off Portland. This was supported by manual and feature space analysis techniques. Increasing song complexity was observed in the form of phrases with broken song units, a phenomenon that was first observed at the Portland site on isolated occasions but has occurred and proliferated in the Perth Canyon area from 2016 onwards. Analysis of environmental conditions indicated that increased background noise due to multiple EIOPB whales vocalising, as well as water depth, may influence song length. This was reflected by songs made up of shorter phrases dominating in higher background noise conditions and deeper water, while longer more complex phrase types dominate in quieter, shallower conditions. Further research is recommended to isolate any potential influence of environmental factors on song production.

Deep embedded clustering of coral reef bioacoustics.

Deep clustering was applied to unlabeled, automatically detected signals in a coral reef soundscape to distinguish fish pulse calls from segments of whale song. Deep embedded clustering (DEC) learned latent features and formed classification clusters using fixed-length power spectrograms of the signals. Handpicked spectral and temporal features were also extracted and clustered with Gaussian mixture models (GMM) and conventional clustering. DEC, GMM, and conventional clustering were tested on simulated datasets of fish pulse calls (fish) and whale song units (whale) with randomized bandwidth, duration, and SNR. Both GMM and DEC achieved high accuracy and identified clusters with fish, whale, and overlapping fish and whale signals. Conventional clustering methods had low accuracy in scenarios with unequal-sized clusters or overlapping signals. Fish and whale signals recorded near Hawaii in February-March 2020 were clustered with DEC, GMM, and conventional clustering. DEC features demonstrated the highest accuracy of 77.5% on a small, manually labeled dataset for classifying signals into fish and whale clusters.

Deep embedded clustering of coral reef bioacoustics

Deep clustering was applied to unlabeled, automatically detected signals in a coral reef soundscape to distinguish fish pulse calls from segments of whale song. Deep embedded clustering (DEC) learned latent features of the signals and formed clusters using fixed-length power spectrograms of the signals. Handpicked spectral and temporal features were also extracted and clustered with Gaussian mixture models (GMM) and conventional clustering. DEC, GMM, and conventional clustering were tested on simulated datasets of fish pulse calls and whale song units with randomized bandwidth, duration, and SNR. Both GMM and DEC achieved high accuracy and identified clusters with fish calls, whale song units, and simultaneous fish calls and whale song units. Conventional clustering methods K-means and hierarchical agglomerative clustering had low accuracy in scenarios with unequally sized clusters or multiple signals. Experimentally detected fish pulse calls and whale song units recorded near Hawaii in February–March 2020 were clustered with DEC, GMM, and conventional clustering. DEC demonstrated the highest accuracy on a small, manually labeled dataset and successfully separated clusters of fish calls and whale song units. GMM achieved high recall for detecting whale song units but accuracy. Both GMM and DEC overpredicted the number of whale song unit signals.

Understanding Effects of Whale-Watching Vessel Noise on Humpback Whale Song in the North Pacific Coast of Colombia With Propagation Models of Masking and Acoustic Data Observations

Soundscapes with minimal anthropogenic noise sources are key for the survival and effective communication of marine mammals. The Gulf of Tribugá is part of the breeding ground for humpback whale Stock G. Currently, no large-scale infrastructure exists on the Gulf's coastline, making it an area with high biodiversity and little anthropogenic noise. Whale-watching is one of the few human activities that contributes to the soundscape. By Morro Mico, on the southern limit of the Utría Natural National Park, an Ecological Acoustic Recorder (EAR, Oceanwide Science Institute) was deployed in the Gulf to record samples of acoustic activity from October to November 2018. It recorded for 10-min intervals with 20-min lapses for a duty cycle of 33.3%. One of the common peak frequencies of humpback whale song units from these recordings was used as input to an acoustic propagation model using the parabolic equation to simulate the communication space of a humpback whale when zero, one, and two boats are present. GPS positions of theodolite data from various whale watching scenarios in the Gulf were used to inform the models. Model results indicate that humpback whale song communication space could be reduced by as much as 63% in the presence of even one whale-watching boat. The boats traveling through the Gulf are the same as those used in whale-watching, and their engine noise while passing Morro Mico coincided with song structural and temporal changes observed in the acoustic data. Combiningin situdata with acoustic models can advance the understanding of the spatio-temporal acoustic reactions of whales when their vocalizations are masked by boat noise. This project serves as an approximation of how humpback whale Stock G may respond to whale-watching vessel noise in the Gulf of Tribugá.

Geographically distinct blue whale song variants in the Northeast Pacific

The Northeast Pacific (NEP) population of blue whalesBalaenoptera musculus musculusis currently managed as a single stock. We investigated the fine-scale frequency characteristics of 1 NEP blue whale song unit, the B call. We analyzed B calls from passive acoustic data collected between 2010 and 2013 at 2 low-latitude sites, Palmyra Atoll and the Hawaiian Islands, and 3 higher-latitude sites, off southern California, off Washington state and in the Gulf of Alaska. Frequency measurements were extracted along the contour of the third harmonic from each call, and data from each region were compared. Calls from the Gulf of Alaska and Hawai‘i presented a downshift in frequency, beginning just past the midway point of the contour, which was not present in calls recorded from southern California or Palmyra Atoll. Calls from Washington displayed intermediate characteristics between those from the other 2 high-latitude sites. Cluster analysis resulted in consistent grouping of call contours from Washington and southern California, in what we termed the NEP B1 variant, while contours from Hawai‘i and the Gulf of Alaska were grouped together, as a NEP B2 variant. Frequency differences were also observed among the variants; the Gulf of Alaska displayed the highest frequency on average, followed by Washington, then southern California. Consistent with other studies, a yearly decline in the frequency of B calls was also observed. This discovery of at least 2 geographically distinct variants provides the first evidence of vocally distinct subpopulations within the NEP, indicating the possibility of a need for finer-scale population segmentation.

Humpback whale song analysis based on automatic classification performance

Song is a prevalent behavior in humpback whale populations, even in regions that are considered to be foraging habitat such as the Monterey Bay National Marine Sanctuary in the Northeast Pacific, where song is detected nine months out of the year. In this work, we explore various machine learning methods to classify song units, as a basis for studying song structure and its changes. We report on a number of analyses and classification exercises based on linear predictive coding, vector quantization, and machine learning classifiers including Naive Bayes, first-order Markov chain, and Hidden Markov modeling. As a baseline for comparison purposes, the distortion measure used to create the codebooks for vector quantization is itself also used as a means for classification. With classification accuracy ranging from 65% to 83% across the selected methods on a 4.5 h recording involving 5000 unit occurrences over 20 different unit types, we evaluate the effect of several signal processing, clustering, and learning parameters on classification performance with the goal of laying a foundation that can be used to characterize song vocalization at not only the unit level but also below (subunit) and above (phrase, theme, song).

The Lombard effect in singing humpback whales: Source levels increase as ambient ocean noise levels increase.

Many animals increase the intensity of their vocalizations in increased noise. This response is known as the Lombard effect. While some previous studies about cetaceans report a 1 dB increase in the source level (SL) for every dB increase in the background noise level (NL), more recent data have not supported this compensation ability. The purpose of this study was to calculate the SLs of humpback whale song units recorded off Hawaii and test for a relationship between these SLs and background NLs. Opportunistic recordings during 2012-2017 were used to detect and track 524 humpback whale encounters comprised of 83 974 units on the U.S. Navy's Pacific Missile Range Facility hydrophones. Received levels were added to their estimated transmission losses to calculate SLs. Humpback whale song units had a median SL of 173 dB re 1 μPa at 1 m, and SLs increased by 0.53 dB/1 dB increase in background NLs. These changes occurred in real time on hourly and daily time scales. Increases in ambient noise could reduce male humpback whale communication space in the important breeding area off Hawaii. Since these vocalization changes may be dependent on location or behavioral state, more work is needed at other locations and with other species.

The Song Structure of the Siberian Rubythroat Luscinia [Calliope] Calliope: Branching Syntax Underlies Complex and Variable vocalization

Abstract The syntactical organization of the avian song is of particular interest in light of recently discussed analogies between the songs of birds and human speech. We present here a description of the song structure of the Siberian Rubythroat Calliope calliope, a small insectivorous bird, widespread in Siberia and the Russian Far East. This species sings predominantly discontinuously, but the duration of individual songs varies significantly. Each individual song is composed of a number of song units, a stereotypical set of different notes and syllables that are always presented together and in a strictly fixed order. Although the variety of song units in an individual's repertoire is significant, the diversity of units presented in the very beginning of individual songs was found to be much more limited. The song of the Siberian Rubythroat is not only extremely complex and variable, but it is also organized as a set of clusters rooted in strictly defined initial song units. Each cluster in turn contains several branching points with a limited number of branches. Despite its impressive variety, the rubythroat's song nevertheless contains numerous fixed sequences of song units.

Inter-annual decrease in pulse rate and peak frequency of Southeast Pacific blue whale song types

A decrease in the frequency of two southeast Pacific blue whale song types was examined over decades, using acoustic data from several different sources in the eastern Pacific Ocean ranging between the Equator and Chilean Patagonia. The pulse rate of the song units as well as their peak frequency were measured using two different methods (summed auto-correlation and Fourier transform). The sources of error associated with each measurement were assessed. There was a linear decline in both parameters for the more common song type (southeast Pacific song type n.2) between 1997 to 2017. An abbreviated analysis, also showed a frequency decline in the scarcer southeast Pacific song type n.1 between 1970 to 2014, revealing that both song types are declining at similar rates. We discussed the use of measuring both pulse rate and peak frequency to examine the frequency decline. Finally, a comparison of the rates of frequency decline with other song types reported in the literature and a discussion on the reasons of the frequency shift are presented.

Variations in received levels on a sound and movement tag on a singing humpback whale: Implications for caller identification.

Bio-logging devices are advancing the understanding of marine animal behavior, but linking sound production and behavior of individual baleen whales is still unreliable. Tag placement potentially within the near field of the sound source creates uncertainty about how tagged animal sounds will register on recorders. This study used data from a tagged singing humpback whale to evaluate this question of how sound levels present on a tag when calls are produced by a tagged animal. Root-mean-square (rms) received levels (RLs) of song units ranged from 112 to 164 dB re 1 μPa rms, with some, but not all, of the lower frequency units registering on the tag's 800 Hz accelerometer sensor. Fifty-nine percent of recorded units measured lower acoustic RLs than previously reported source levels for humpback song, but signal-to-noise ratios (SNRs) were 30-45 dB during periods of the dive with low noise. This research highlights that tag RL does not alone predict caller identity, argues for higher SNR thresholds if using SNR to inform decisions about the source of a call, and provides a baseline for future research identifying diagnostic properties of tagged animal calls in cetacean bioacoustic tag datasets.